By virtue of recent advances in digital technology, it has become possible to convert a radiation image to a digital image signal, subject the digital image signal to image processing and display the image on a CRT or print out the image using a printer. In photography for acquiring the radiation image, it is desired that the X-ray dose at the time of photography be small in view of the effects of X-rays upon the patient. However, it is known that an image captured with a reduced X-ray dose contains a large quantity of quantization noise, and there is the possibility that such quantization noise will be a hindrance to diagnosis. For this reason, processing for eliminating such noise has been studied. Examples are noise elimination processing that uses a simple median filter, and a method (referred to as “filter processing”) of eliminating noise by extracting high-frequency components using a smoothed image. In recent years, consideration has been given to multiplexed frequency processing for dividing an input image into a plurality of frequency bands and applying independent processing on a per-frequency-band basis to thereby eliminate noise.
With filter processing for eliminating noise by extracting high-frequency components using a smoothed image, a single frequency band is used. In a case where noise components are distributed over a wide frequency band, therefore, noise cannot be eliminated effectively. In order to avoid this, multiple filters having different sizes (namely different frequencies) are utilized simultaneously. However, this leads to a major increase in the cost of calculations necessary for processing. In addition, in order that the frequency characteristics of the filters must be optimized for eliminating noise, adjustment of filter size in accordance with the subject is essential. The problem that arises as a result is a decline in general versatility.
The above-mentioned problems are largely mitigated by using multiplexed frequency processing for noise elimination. However, since data in the same image is processed uniformly, it is difficult to optimally process areas of good transparency and areas of poor transparency as well as areas with much fine texture and areas in which almost no texture exists.
The present invention has been made in consideration of the above problem, and has as its object to eliminate a noise by acquiring the transform coefficient of wavelet transform based on the information of the image data in a rectangle area, acquiring the image data base on the transformation coefficient.